A New Palm Print Recognition Approach by Using PCA & Gabor Filter

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Deepali Koul, Satish Kumar Alaria

Abstract

The key problems that involve in identification of palm print are searching for the better match from the test sample taken from input and also the available templates in the palm print database. The selection of the features and measuring similarity are 2 basic to be resolved. A feature that has higher discriminating ability should need to show a large variation between samples taken from totally different persons and small variation between samples taken from the palm of same person. Principal lines with information points are consider as very helpful palm print features and are successfully used for the aim of verification. Excluding these features there are many various features present in a palm print like: wrinkle features, geometry features, minutiae features and delta point features. It�s noted that each one of those features of palm are involved with the native attributes supported points or line segments. 2 key points in palm print identification are: first is to develop an efficient algorithm that extracts helpful features and second is to correctly measure the similarity of 2 features sets. In contrast to the existing technique, propose a combine selection technique for identification by using the palm print feature base pattern matching by combining native and global palm print features in some stratified fashion. In this work, use PCA, Gabor Filter and KNN for the aim of classification and matching. This work show palm print authentication system operates in 2 ways in which first is enrolment and the second is verification. In enrolment, a user needs to offer palm print samples many times to the system. The samples is captured with the use of any image capturing device that then pre-processed and so extraction of features is done to provide the templates that keep template database. For verification user is instruct to produce his/her user ID and palm print sample, then the palm print sample are pre-processed and extraction of feature is done to compared it with templates keep within the database that belonging to constant user ID.

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How to Cite
, D. K. S. K. A. (2018). A New Palm Print Recognition Approach by Using PCA & Gabor Filter. International Journal on Future Revolution in Computer Science &Amp; Communication Engineering, 4(4), 38–45. Retrieved from https://ijfrcsce.org/index.php/ijfrcsce/article/view/1464
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